The impact of India’s food security policy on domestic and international rice market

Food security policy making in India is at crossroads. India has emerged as a leading rice exporter. The Government of India has introduced the National Food Security Act which requires 33.6 million tons of rice per year for its public food distribution system. In this study, we modeled India’s rice market and analyzed policy implications of the long-term impact of India’s food security act on domestic and international rice market. We developed a structural economic demand and supply model for India’s rice market and further added subsidy equations to trace the consequence of National Food Security Act on domestic rice consumption and on the international market. We specifically focus on three different scenarios: subsidy as price effect, subsidy as inelastic income effect, and subsidy as elastic income effect under the broader framework of National Food Security Act. We found that at the end of the projection period (2024–2025), as a result of rice subsidy program, the consumption of rice increases significantly in the case of price effect while the inelastic income effect has no or less impact on production, consumption, and export of rice. Hence, the policy implication of our study is that if the objective of the National Food Security Act is to increase consumption then it needs to be implemented as price effect.     

The role of standards in the policy debate on the EU-US trade agreement

In the context of the public policy debate, we explore firm-level characteristics that influence firms’ preferences related to alternatives to harmonize standards within the Transatlantic Trade and Investment Partnership (TTIP). The options are the implementation of common standards, developed internationally or bilaterally, and mutual recognition. The empirical analysis is based on data from the German Standardization Panel. We identify three dimensions that determine firms’ preferences regarding the various harmonization solutions: (1) company-specific factors, such as size, industry and motives to apply standards, (2) the competitive environment, i.e. the position vis-à-vis other market participants, and (3) the technological environment, i.e. the dynamics of the market the company operates in.     

Uncovering peer effects mechanisms with weight outcomes using spatial econometrics

Research about how peers influence weight outcomes among adolescents has yielded mixed findings. This paper seeks to not only estimate these peer effects, but also to distinguish between two mechanisms: social multiplier effects and social norm effects. After estimating an augmented spatial autoregressive model using data from the National Longitudinal Study of Adolescent to Adult Health Survey, this study finds significant peer interactions in body mass index, which can be explained by both mechanisms of peer influence; the social norm effect is much larger than the social multiplier effect. The estimated peer effects for overweight and obesity statuses suggest that peer effects are important for overweight status but not for obesity status, and peer influence for overweight status appears to operate solely through social multiplier effect. These findings provide important information for the design of obesity-prevention interventions in schools.     

Non‐parametric interval estimation for the partial area under the ROC curve

Accurate diagnosis of disease is a critical part of health care. New diagnostic and screening tests must be evaluated based on their abilities to discriminate diseased conditions from non‐diseased conditions. For a continuous‐scale diagnostic test, a popular summary index of the receiver operating characteristic (ROC) curve is the area under the curve (AUC). However, when our focus is on a certain region of false positive rates, we often use the partial AUC instead. In this paper we have derived the asymptotic normal distribution for the non‐parametric estimator of the partial AUC with an explicit variance formula. The empirical likelihood (EL) ratio for the partial AUC is defined and it is shown that its limiting distribution is a scaled chi‐square distribution. Hybrid bootstrap and EL confidence intervals for the partial AUC are proposed by using the newly developed EL theory. We also conduct extensive simulation studies to compare the relative performance of the proposed intervals and existing intervals for the partial AUC. A real example is used to illustrate the application of the recommended intervals. The Canadian Journal of Statistics 39: 17–33; 2011 © 2011 Statistical Society of Canada     

Multivariate spatial U-quantiles: A Bahadur–Kiefer representation,a Theil–Sen estimator for multiple regression,and a robust dispersion estimator

A leading multivariate extension of the univariate quantiles is the so-called “spatial” or “geometric” notion, for which sample versions are highly robust and conveniently satisfy a Bahadur–Kiefer representation. Another extension of univariate quantiles has been to univariate U-quantiles, on the basis of which, for example, the well-known Hodges–Lehmann location estimator has a natural formulation. Generalizing both extensions, we introduce multivariate spatial U-quantiles and develop a corresponding Bahadur–Kiefer representation. New statistics based on spatial U-quantiles are presented for nonparametric estimation of multiple regression coefficients, extending the classical Theil–Sen nonparametric simple linear regression slope estimator, and for robust estimation of multivariate dispersion. Some other applications are mentioned as well.     

Minimum phi-divergence estimators for loglinear models with linear constraints and multinomial sampling

In this paper the family ofφ-divergence estimators for loglinear models with linear constraints and multinomial sampling is studied. This family is an extension of the maximum likelihood estimator studied by Haber and Brown (1986). A simulation study is presented and some alternative estimators to the maximum likelihood are obtained. This work was parcially supported by Grant DGES PB2003-892     

Star-shaped distributions and their generalizations

Elliptically contoured distributions can be considered to be the distributions for which the contours of the density functions are proportional ellipsoids. We generalize elliptically contoured densities to “star-shaped distributions” with concentric star-shaped contours and show that many results in the former case continue to hold in the more general case. We develop a general theory in the framework of abstract group invariance so that the results can be applied to other cases as well, especially those involving random matrices.     

Analysis of middle-censored data with exponential lifetime distributions

Recently Jammalamadaka and Mangalam [2003. Non-parametric estimation for middle censored data. J. Nonparametric Statist. 15, 253–265] introduced a general censoring scheme called the “middle-censoring” scheme in non-parametric set up. In this paper we consider this middle-censoring scheme when the lifetime distribution of the items is exponentially distributed and the censoring mechanism is independent and non-informative. In this set up, we derive the maximum likelihood estimator and study its consistency and asymptotic normality properties. We also derive the Bayes estimate of the exponential parameter under a gamma prior. Since a theoretical construction of the credible interval becomes quite difficult, we propose and implement Gibbs sampling technique to construct the credible intervals. Monte Carlo simulations are performed to evaluate the small sample behavior of the techniques proposed. A real data set is analyzed to illustrate the practical application of the proposed methods.